An Inverse Optimization Approach of Vehicle Routing Problem

被引：0
|
作者：
Chen Y. [1 ]
Chen L. [1 ]
机构：
[1] School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai
来源：
Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University | 2022年 / 56卷 / 01期
关键词：
Cost matrix; Experience learning; Inverse optimization; Vehicle routing problem(VRP);
D O I：
10.16183/j.cnki.jsjtu.2020.210
中图分类号：
学科分类号：
摘要：
Generally, experienced drivers or experts do not always follow the shortest path in the last mile delivery of e-commerce. Hence, an inverse optimization approach was proposed to obtain a proper cost matrix by learning from the experts' past experience. Thus, the routing model with respect to the learned cost matrix could provide solutions as good as those given by experts. An algorithm-based multiplicative weights updates algorithm was applied to achieve the experience learning process. The experimental analyses based on the random and real-life instances demonstrate the effectiveness of this approach. © 2022, Editorial Board of Journal of Shanghai Jiao Tong University. All right reserved.
引用
收藏
页码：81 / 88
页数：7
相关论文
共 25 条
  • [11] HE Z C, CHEN K Y, CHEN X Y., A collaborative method for route discovery using taxi drivers' experience and preferences, IEEE Transactions on Intelligent Transportation Systems, 19, 8, pp. 2505-2514, (2018)
  • [12] HUANG Min, MAO Feng, QIAN Yuxiang, Mining fastest route using taxi drivers' experience via constrained deep reinforcement learning, Application Research of Computers, 37, 5, pp. 1298-1302, (2020)
  • [13] AHUJA R K, ORLIN J B., Combinatorial algorithms for inverse network flow problems, Networks, 40, 4, pp. 181-187, (2002)
  • [14] AHUJA R K, ORLIN J B., Inverse optimization, Operations Research, 49, 5, pp. 771-783, (2001)
  • [15] ZHANG J Z, LIU Z H., Calculating some inverse linear programming problems, Journal of Computational and Applied Mathematics, 72, 2, pp. 261-273, (1996)
  • [16] ZHANG J Z, LIU Z H., A general model of some inverse combinatorial optimization problems and its solution method under l<sub>∞</sub> norm, Journal of Combinatorial Optimization, 6, 2, pp. 207-227, (2002)
  • [17] HEUBERGER C., Inverse combinatorial optimization: A survey on problems, methods, and results, Journal of Combinatorial Optimization, 8, 3, pp. 329-361, (2004)
  • [18] YOU S I, CHOW J Y J, RITCHIE S G., Inverse vehicle routing for activity-based urban freight forecast modeling and city logistics, Transportmetrica A: Transport Science, 12, 7, pp. 650-673, (2016)
  • [19] MOU Jianhui, GUO Qianjian, GAO Liang, Et al., Multi-objective genetic algorithm for solving multi-objective flow-shop inverse scheduling problems, Journal of Mechanical Engineering, 52, 22, pp. 186-197, (2016)
  • [20] BARMANN A, MARTIN A, POKUTTA S, Et al., An online-learning approach to inverse optimization
123